Channel state information reporting with basis expansion for advanced wireless communications systems

ABSTRACT

Scalable channel state information feedback for FD-MIMO involves quantizing the downlink channel according to a finite set of basis vectors to reduce the number of coefficients quantized and reported from a user equipment to a base station. The procedure includes measurement at the base station of angle of arrival spread for uplink signal reception from the user equipment and signaling that spread to the user equipment. The user equipment then quantizes the MIMO channel according to a sub-scheme configured based upon the signaled spread and reports (feeds back) the quantized channel to the base station.

This application claims priority to and hereby incorporates by referenceU.S. Provisional Patent Application No. 62/048,729, filed Sep. 10, 2014,entitled “CHANNEL STATE INFORMATION REPORTING WITH BASIS EXPANSION FORADVANCED WIRELESS COMMUNICATION SYSTEMS” and U.S. Provisional PatentApplication No. 62/059,664, filed Oct. 3, 2014, entitled “CODEBOOKDESIGN AND FEEDBACK PROCEDURES FOR ADVANCED WIRELESS COMMUNICATIONSYSTEMS.”

TECHNICAL FIELD

The present disclosure relates generally to reporting channel stateinformation in a wireless communication system and, more specifically,to reporting channel state information associated with multiple transmitantennas. Such two dimensional arrays are associated with a type ofmultiple-input-multiple-output (MIMO) system often termed“full-dimension” MIMO (FD-MIMO).

BACKGROUND

Existing channel quality reporting processes in wireless communicationssystems do not sufficiently accommodate reporting of channel stateinformation associated with large, two dimensional array transmitantennas.

There is, therefore, a need in the art for improved channel qualityreporting in wireless communications systems.

SUMMARY

Scalable channel state information feedback for FD-MIMO involvesquantizing the downlink channel according to a finite set of basisvectors to reduce the number of coefficients quantized and reported froma user equipment to a base station. The procedure includes measurementat the base station of angle of arrival spread for uplink signalreception from the user equipment and signaling that spread to the userequipment. The user equipment then quantizes the MIMO channel accordingto a sub-scheme configured based upon the signaled spread and reports(feeds back) the quantized channel to the base station.

Before undertaking the DETAILED DESCRIPTION below, it may beadvantageous to set forth definitions of certain words and phrases usedthroughout this patent document: the terms “include” and “comprise,” aswell as derivatives thereof, mean inclusion without limitation; the term“or,” is inclusive, meaning and/or; the phrases “associated with” and“associated therewith,” as well as derivatives thereof, may mean toinclude, be included within, interconnect with, contain, be containedwithin, connect to or with, couple to or with, be communicable with,cooperate with, interleave, juxtapose, be proximate to, be bound to orwith, have, have a property of, or the like; and the term “controller”means any device, system or part thereof that controls at least oneoperation, where such a device, system or part may be implemented inhardware that is programmable by firmware or software. It should benoted that the functionality associated with any particular controllermay be centralized or distributed, whether locally or remotely.Definitions for certain words and phrases are provided throughout thispatent document, those of ordinary skill in the art should understandthat in many, if not most instances, such definitions apply to prior, aswell as future uses of such defined words and phrases.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present disclosure and itsadvantages, reference is now made to the following description taken inconjunction with the accompanying drawings, in which like referencenumerals represent like parts:

FIG. 1 illustrates a portion of an advanced wireless communicationsystem within which channel state information reporting with basisexpansion may be implemented in accordance with various embodiments ofthe present disclosure;

FIG. 1A represents an exemplary antenna array within the wirelesscommunication system of FIG. 1;

FIG. 2 illustrates the subset of elevation dimensions for channel stateinformation reporting with basis expansion in accordance with variousembodiments of the present disclosure, where a similar visualizationapplied to azimuthal dimensions;

FIG. 3 illustrates a coordinate system for use in connection withchannel state information reporting with basis expansion in accordancewith various embodiments of the present disclosure;

FIG. 4 illustrates an exemplary scalar codebook for use in connectionwith channel state information reporting with basis expansion inaccordance with various embodiments of the present disclosure;

FIG. 5 illustrates an exemplary 2D codebook for use in connection withchannel state information reporting with basis expansion in accordancewith various embodiments of the present disclosure;

FIG. 6 illustrates data sets employed for training-based construction ofcodebooks for use in connection with channel state information reportingwith basis expansion in accordance with various embodiments of thepresent disclosure; and

FIGS. 7A and 7B illustrate two exemplary operations for overalltransmit-receive operations at the eNB and the UE in accordance with oneembodiment of the present disclosure.

DETAILED DESCRIPTION

FIGS. 1 through 7B, discussed below, and the various embodiments used todescribe the principles of the present disclosure in this patentdocument are by way of illustration only and should not be construed inany way to limit the scope of the disclosure. Those skilled in the artwill understand that the principles of the present disclosure may beimplemented in any suitably arranged wireless communication system.

The following documents are hereby incorporated herein by reference:[REF1] 3GPP TS36.211; [REF2] 3GPP TS36.212; and [REF3] 3GPP TS36.213.

LIST OF ACRONYMS

2D: two-dimensional

MIMO: multiple-input-multiple-output

SU-MIMO: single-user MIMO

MU-MIMO: multi-user MIMO

3GPP: 3rd generation partnership project

LTE: long-term evolution

UE: user equipment

eNB: evolved Node B or “eNodeB”

DL: downlink

UL: uplink

CRS: cell-specific reference signal(s)

DMRS: demodulation reference signal(s)

SRS: sounding reference signal(s)

UE-RS: UE-specific reference signal(s)

CSI-RS: channel state information reference signals

SCID: scrambling identity

MCS: modulation and coding scheme

RE: resource element

CQI: channel quality information

PMI: precoding matrix indicator

RI: rank indicator

MU-CQI: multi-user CQI

CSI: channel state information

CSI-IM: CSI interference measurement

CoMP: coordinated multi-point

DCI: downlink control information

UCI: uplink control information

PDSCH: physical downlink shared channel

PDCCH: physical downlink control channel

PUSCH: physical uplink shared channel

PUCCH: physical uplink control channel

PRB: physical resource block

RRC: radio resource control

AoA: angle of arrival

AoD: angle of departure

The need for high-performance, scalable (with respect to the number andgeometry of transmit antennas), and flexible CSI feedback framework andstructure for LTE enhancements when FD-MIMO (the use of largetwo-dimensional antenna arrays) is supported. To achieve highperformance, more accurate CSI (in terms of quantized MIMO channel) isneeded at the eNB, especially for FDD scenarios. In this case, theprecoding framework (PMI-based feedback) of previous LTE (e.g. Rel.12)may need to be replaced. However, feeding back the quantized channelcoefficients may be excessive in terms of feedback requirements. In thisdisclosure, the following properties of FD-MIMO are factored in for theproposed alternative feedback schemes:

-   -   The use of closely spaced large 2D antenna arrays (primarily        geared toward high beamforming gain rather than spatial        multiplexing) along with relatively small angular spread for        each UE: This allows “compression” or “dimensionality reduction”        of the quantized channel feedback based on a fixed set of basis        functions/vectors.    -   Low mobility as the target scenario for FD-MIMO: Possibility to        update channel quantization parameters (such as the channel        angular spreads) at a low rate, e.g. using UE-specific        higher-layer signaling. In addition, CSI feedback can also be        performed cumulatively.

In the present disclosure, a scalable and FDD-enabling CSI feedbackscheme for FD-MIMO is described where the downlink channel is quantizedaccording to a finite set of basis functions/vectors to reduce thenumber of coefficients that need to be quantized and reported from a UEto the eNB. The high-level procedure of the proposed scheme is asfollows (assuming the use of 2D antenna array):

-   -   From reception of at least one UL signal (e.g., UL-SRS,        UL-DMRS), the eNB measures an associated UL AoA spread        associated with each UE, denoted as [θ_(min), θ_(max)] and/or        [φ_(min), φ_(max)] in the elevation (zenith) and/or azimuthal        dimensions, respectively. These parameters for (or, in general,        are parts of) a UL AoA profile associated with that particular        UE.        -   The acquired AoA values (θ_(min), θ_(max), φ_(min), φ_(max))            or profile are signaled to the UE via a UE-specific medium            such as higher-layer RRC signaling or dynamic-BCH (D-BCH).            Some other parameters may be signaled as well. These            configuration parameters are associated with the choice of            channel quantization sub-scheme (corresponding to a reduced            subset of basis functions/vectors).    -   Upon receiving configuration parameter(s), the UE quantizes the        MIMO channel according to the configured sub-scheme and reports        (feeds back) the quantized channel to the eNB via an uplink        channel.    -   The three steps listed above are repeated whenever the eNB        updates the configuration parameters.

The proposed CSI feedback upgrade is intrusive as it requires somesignificant amount of additional standardization. It is a considerabledeparture from the Rel.12 LTE CSI feedback paradigm. However, as thesize of antenna array increases, such an evolution path is eventuallyinevitable if high-performance FD-MIMO is a goal of the future evolutionof LTE—especially in FDD scenarios.

Advantages of the approach described in the present disclosure includeoverhead reduction from quantizing coefficients to a significantlysmaller number through subspace reduction, compared to direct channelquantization, as described above. It is also possible to derive thebasis functions/vectors at the UE using, e.g., eigen-vectordecomposition (EVD) or singular-value decomposition (SVD) and feed themback to the eNB. However, EVD/SVD precoders are known to be sensitive toerror (which results in unintentional signal space cancellation) evenwhen regularization is employed. In this sense, a fixed set of basisfunctions/vectors tends to be more robust.

FIG. 1 illustrates a portion of an advanced wireless communicationsystem within which CSI reporting with basis expansion may beimplemented in accordance with various embodiments of the presentdisclosure. The wireless communication system 100 includes at least onebase station (BS) 101 (also sometimes referred to as “NodeB,” “evolvedNodeB” or “eNB”), and generally a plurality of base stations (notshown). User equipment UE0 (also sometimes referred to as a “mobilestation” or “MS”) communicates wirelessly with the base station 101. Inthe exemplary embodiment, at least one of the base station 101 and theuser equipment UE0 includes an antenna array as described below. Each ofthe base station 101 and the user equipment UE0 includes a processor (orprogrammable controller or the like) coupled to a wireless transceiverand configured to control transmission and reception of signals via thetransceiver, as well as to perform various functions associated withpreparing signals for transmission and/or processing received signals,such as demodulation, decoding, etc. The wireless transceivers of eachof base station 101 and user equipment UE0 are coupled to an antenna,which for at least base station 101 (and possibly also user equipmentUE0) is an antenna array.

FIG. 1A represents an exemplary two dimensional (2D) antenna arrayconstructed from 16 dual-polarized antenna elements arranged in a 4×4rectangular format. In this example, each labelled antenna element islogically mapped onto a single antenna port. In general, one antennaport may correspond to multiple antenna elements (physical antennas)combined via a virtualization scheme. The 4×4 dual polarized arrayrepresented in FIG. 1A can then be viewed as 16×2=32-element array ofantenna elements. The vertical dimension (consisting of 4 rows)facilitates elevation beamforming, and is in addition to the azimuthalbeamforming across the horizontal dimension (consisting of 4 columns ofdual polarized antennas). MIMO precoding in Rel.12 LTE standardization(per TS36.211 section 6.3.4.2, 6.3.4.4, and TS36.213 section 7.2.4) waslargely designed to offer precoding gain for one-dimensional antennaarray. While fixed beamforming (i.e., antenna virtualization) can beimplemented across the elevation dimension, it is unable to reap thepotential gain offered by the spatial and frequency selective nature ofthe channel.

In Rel.12 LTE, MIMO precoding (for spatial multiplexing) can beperformed either with CRS (cf. TS36.211 section 6.3.4.2) or UE-RS (cf.TS36.211 section 6.3.4.4). In either case, each UE operating in spatialmultiplexing mode(s) is configured to report CSI which may contain PMI(i.e. precoding codebook index). PMI report is derived from one of thefollowing sets of standardized codebooks:

-   -   Two antenna ports: {TS36.211 table 6.3.4.2.3-1}    -   Four antenna ports: {TS36.211 table 6.3.4.2.3-2} or {TS36.213        table 7.2.4-0A, B, C, and D}    -   Eight antenna ports: {TS36.213 table 7.2.4-1, 2, 3, 4, 5, 6, 7,        and 8}        If the eNB follows the UE's PMI recommendation, the eNB is        expected to precode its transmitted signal according to the        recommended precoding vector/matrix (for a given subframe and        PRB). Regardless whether the eNB follows the UE's        recommendation, the UE is configured to report a PMI according        to the above precoding codebooks. Here a PMI (which may consist        of a single index or a pair of indices) is associated with a        precoding matrix W of size N_(c)×N_(L), where N_(c) is the        number of antenna ports in one row (=number of columns) and        N_(L) is the number of transmission layers. As the number of        antenna elements increases (e.g., up to 8 rows of four        dual-polarized antennas which amounts to 64 elements),        significantly larger precoding codebooks are needed. In        addition, as MU-MIMO becomes a dominant scheduling strategy,        obtaining a good multi-user pairing from single-user PMIs        (received from the active UEs) has proved to be challenging.        Hence, the Rel.12 LTE CSI feedback paradigm limits the potential        of FD-MIMO especially in FDD scenarios where channel reciprocity        is limited to long-term channel statistics at best.

Therefore, for FD-MIMO that utilizes 2D antenna array (hence 2Dprecoding), the need for high-performance, scalable (with respect to thenumber and geometry of transmit antennas), and flexible CSI feedbackframework and structure is evident. To achieve high performance, moreaccurate CSI (preferably in terms of quantized MIMO channel) is neededat the eNB. This is especially the case for FDD scenarios whereshort-term reciprocity is infeasible. In this case, the previous LTE(e.g. Rel.12) precoding framework (PMI-based feedback) may need to bereplaced. At the same time, however, feeding back the quantized channelcoefficients may be excessive in terms of feedback requirements.

In this disclosure, the following properties of FD-MIMO are factored infor our proposed schemes:

-   -   The use of closely spaced large 2D antenna arrays (primarily        geared toward high beamforming gain rather than spatial        multiplexing) along with relatively small angular spread for        each UE: This allows “compression” or “dimensionality reduction”        of the quantized channel feedback. In this case, a set of basis        functions/vectors is used and quantization is basically        expressing the MIMO channel in terms of a linear combination of        those basis functions/vectors.    -   Low mobility as the target scenario for FD-MIMO: This        alternative exploits the possibility to update quantization        parameters (long-term channel statistics such as channel angular        spread) at a low rate, e.g., using UE-specific higher-layer        signaling. In addition, CSI feedback can also be performed        cumulatively.    -   While time-varying basis functions/vectors can be used (e.g.,        derived from EVD or SVD and fed back from the UE to the eNB),        small channel angular spread warrants the use of a fixed        master-set of basis functions/vectors derived primarily from the        channel characteristics. For a given channel angular spread        characteristic, a subset of the fixed master-set (where the        master-set is pre-known both at the UE and the eNB) is chosen by        the eNB and signaled to the UE.

The procedure for operating the proposed channel feedback scheme is asfollows:

-   -   From the UL signal reception (in terms of, e.g., UL-SRS,        UL-DMRS), the eNB measures the AoA spread associated with each        UE, denoted as [θ_(min), θ_(max)] and/or [φ_(min), φ_(max)] in        the elevation (zenith) and azimuthal dimensions, respectively.        Here, two alternatives are possible.        -   Alt1: The eNB performs AoA estimation/measurement by            scanning through the entire range of AoA values. This yields            a rough AoA profile which allows the eNB to estimate the            range of AoAs. By reciprocity of long-term channel            statistics, the range of UL AoAs represents the range of DL            AoDs for a particular UE.            -   This UL measurement can be performed with the same (2D)                antenna array as that used for DL transmissions, or a                subset of the available antenna elements.        -   Alt2: Alternatively, instead of the eNB, it is possible for            the UE to measure the range of AoAs (or any other feedback            parameters associated with it) and reports that range to the            eNB via an UL channel. This solution, however, requires an            additional standardization support.        -   While the above discussion assumes the use of a single            angular cone of AoDs defined by f{(φ,θ):            φε[φ_(min),φ_(max)]̂θε[θ_(min),θ_(max)]}, it is also possible            for the eNB to configure the UE for a plurality of cones            whenever appropriate.    -   Regardless whether Alt1 or Alt2 is chosen, the        acquired/estimated DL AoD values (θ_(min), θ_(max), φ_(min),        φ_(max)), or their representation, are signaled to the UE via a        UE-specific medium such as higher-layer RRC signaling or dynamic        broadcast channel (D-BCH). It is also possible to utilize PDCCH        (see below for further details). Some other quantization        parameters may be signaled as well (see below for further        details and alternatives). These configuration parameters are        associated with the choice of channel quantization sub-scheme        (corresponding to a reduced subset of basis functions/vectors).    -   Upon receiving configuration parameter(s), the UE quantizes the        DL MIMO channel according to the configured sub-scheme and        reports (feeds back) the quantized channel to the eNB via an        uplink channel.        -   The quantized DL channel coefficients can be reported to the            eNB via an UL channel such as PUCCH or PUSCH. With PUCCH, a            new periodic reporting mechanism may need to be defined            (here, multiple PUCCH resources may be needed). With PUSCH,            the existing aperiodic PUSCH-based reporting can be utilized            where the eNB triggers the UE to report quantized DL channel            coefficients via a UL grant.        -   The configured sub-scheme is based on a subset of basis            functions/vectors chosen from the master-set, based on the            channel representation parameters (see below for further            details).        -   For the 2D antenna array (in case of FD-MIMO), the            quantization of the channel matrix H^((q,f)) associated with            each polarization (+45° or −45°), the q-th receive antenna            (at the UE), and f-th subband amounts to computing the            expansion coefficients

{c_(k, l)^((q, f))}_(k, l)

-   -   relative to the basis set {A(φ_(k),θ_(l))}_(k,l) in equation        (1). Here H^((q,f)) is an N_(r)×N_(c) matrix, where N_(r) and        N_(c) are the number of rows (corresponding to the azimuthal        angle φ) and columns (corresponding to the elevation angle θ) in        the 2D array, respectively. The numbering of antenna ports        follows that in FIG. 1A.        -   In some embodiments, the subset of angles            {(φ_(k),θ_(l))}_(k,l) are chosen to cover the range of AoDs            [θ_(min),θ_(max)] and [φ_(min),φ_(max)]. The N_(r)×N_(c)            matrix is the transmit antenna array response A(φ_(k),            θ_(l)) for a given pair of AoDs. In case of multiple-cone            configuration, equation (1) is applied to each of the            plurality of cones.

H ^((q,f))≅Σ_(k=k) ₀ ^(k) ⁰ ^(+K−1)Σ_(l=l) ₀ ^(l) ⁰ ^(+L−1) c _(k,l)^((q,f)) A(φ_(k),θ_(l))  (1)

-   -   In some embodiments, a subset of pair of angles Ω={(φ_(k),        θ_(l))} are chosen to represent a plurality of cones, wherein        the elements of the subset are one-to-one mapped to the        plurality of cones (represented by ω). The N_(r)×N_(c) matrix is        the transmit antenna array response A(φ_(k), θ_(l)) for the        subset.

H ^((q,f))≅Σ_((k,l)εΩ) c _(k,l) ^((q,f)) A(φ_(k),θ_(l))  (1b)

-   -   The three steps listed above are repeated whenever the eNB        updates the configuration parameters.

EXEMPLARY EMBODIMENTS Choice of Basis Functions/Vectors and itsAssociated Signaling Embodiment 1

For a typical 2D dual-polarized array (see FIG. 1) with a sufficientlysmall inter-element spacing, for each polarization (+45° or −45°), theterm A(φ_(k), θ_(l)) can be written as follows (see FIG. 2 and FIG. 3):

$\begin{matrix}{{A\left( {\varphi_{k},\theta_{l}} \right)} = {{{\frac{1}{\sqrt{N_{r}N_{c}}}\left\lbrack \begin{matrix}1 \\{\exp \left( {j\frac{2\; \pi \; d_{r}{\sin \left( {\theta - {\pi/2}} \right)}}{\lambda}} \right)} \\\vdots \\{\exp \left( {{j\left( {N_{r} - 1} \right)}\frac{2\; \pi \; d_{r}{\sin \left( {\theta - {\pi/2}} \right)}}{\lambda}} \right)}\end{matrix} \right\rbrack}\mspace{191mu}\left\lbrack \begin{matrix}1 \\{\exp \left( {j\frac{2\; \pi \; d_{c}{\cos (\varphi)}}{\lambda}} \right)} \\\vdots \\{\exp \left( {{j\left( {N_{c} - 1} \right)}\frac{2\; \pi \; d_{c}{\cos (\varphi)}}{\lambda}} \right)}\end{matrix} \right\rbrack}^{T}\overset{\bigtriangleup}{=}{{a_{r}(\theta)}{a_{c}^{T}(\varphi)}}}} & (2)\end{matrix}$

Assume that the number of frequency sub-bands and receive antennas atthe UE are N_(F) and N_(RX), respectively. In this case, the number ofchannel coefficients c_(k,l) ^((q,f)) that need to be quantized is2KL×N_(RX)N_(F) instead of 2N_(r)N_(c)×N_(RX)N_(F). When(θ_(max)−θ_(min)) and (φ_(max)−φ_(min)) are relatively small, it isexpected that KL<<N_(r)N_(c) (which results in some savings in feedbackrequirements). This is because for a reasonable time span, alow-mobility UE is localized within a small angular cone of AoDs definedby {(φ,θ): φε[φ_(min),φ_(max)]̂ε[θ_(min), θ_(max)]}.

The proposed scheme operates based on a predetermined master-set ofbasis functions/vectors. This master-set is fixed and constructed tocover the entire range of AoD values, that is, {(φ,θ):φε[φ_(min),φ_(max)]̂θε[θ_(min), θ_(max)]}. For a given number of rows andcolumns (N_(r), N_(c)), at least N_(r) values of θ (preferablywell-spaced spanning [0, π)) and N_(c) values of φ (also preferablywell-spaced spanning [0,2π)) are needed to construct a complete basisset (in multidimensional complex-valued field/space). One possiblecomplete (and tight) master-set can be constructed from uniformly spacedAoD values corresponding to (1) and/or (2):

$\begin{matrix}{{\theta_{l} = {\frac{\pi}{N_{r}}l}},\mspace{14mu} {\varphi_{k} = {\frac{2\; \pi}{N_{c}}k}},\mspace{14mu} {l = 0},1,\ldots \mspace{14mu},{N_{r} - 1},\mspace{14mu} {k = 0},1,\ldots \mspace{14mu},{N_{c} - 1}} & (3)\end{matrix}$

In (3), the number of basis functions in the master-set is N_(r)N_(c).However, for various reasons it is better to have an over-completemaster-set in practice, which can be constructed by oversampling the AoDdimensions. This results in a larger size of master-set. For example,with oversampling factors of Ω_(r) and Ω_(c) (integers >1), thefollowing AoD oversampling scheme can be used to construct a master-setof size Ω_(r)Ω_(c)N_(r)N_(c):

$\begin{matrix}{{\theta_{l} = {\frac{\pi}{\Omega_{\; r}N_{r}}l}},\mspace{11mu} {\varphi_{k} = {\frac{2\; \pi}{{\Omega \;}_{c}N_{c}}k}},\; {l = 0},1,\ldots \mspace{14mu},{{{\Omega \;}_{r}N_{r}} - 1},\; {k = 0},1,\ldots \mspace{14mu},{{{\Omega \;}_{c}N_{c}} - 1}} & (4)\end{matrix}$

Embodiment 2

Notice that (1) and (2) facilitate (or at least encourage) a lineardiscretization in the AoD domain. Alternatively, it is also possible torepresent the MIMO channel as a linear combination of basisfunctions/vectors in the discrete Fourier transform (DFT) phase domain.That is:

$\begin{matrix}{H^{({q,f})} \cong {\sum\limits_{k = k_{0}}^{k_{0} + K - 1}\; {\sum\limits_{l = l_{0}}^{l_{0} + L - 1}\; {c_{k,l}^{({q,f})}B_{k,l}}}}} & (5) \\{B_{k,l} = {{\frac{1}{\sqrt{N_{r}N_{c}}}\begin{bmatrix}1 \\{\exp \left( {j\frac{2\; \pi \; l}{\Delta_{r}N_{r}}} \right)} \\\vdots \\{\exp \left( {{j\left( {N_{r} - 1} \right)}\frac{2\; \pi \; l}{\Delta_{r}N_{r}}} \right)}\end{bmatrix}}\begin{bmatrix}1 \\{\exp \left( {j\frac{2\; \pi \; l}{\Delta_{c}N_{c}}} \right)} \\\vdots \\{\exp \left( {{j\left( {N_{c} - 1} \right)}\frac{2\; \pi \; l}{\Delta_{c}N_{c}}} \right)}\end{bmatrix}}^{T}} & (6)\end{matrix}$

Analogous to the first embodiment, in the case of multiple-coneconfiguration, equations (5) and (6) apply to each of the plurality ofcones.

Similar to (4), Δ_(r) and Δ_(c) in (6) are oversampling factors(integers ≧1, with 1 as a special case of non-overlapping DFT beams)which produce overlapping DFT beams. In that case, the master-setassociated with (5) and (6) is given as follows:

$\begin{matrix}{{B_{k,l} = {{\frac{1}{\sqrt{N_{r},N_{c}}}\begin{bmatrix}1 \\{\exp \left( {j\frac{2\; \pi \; l}{\Delta_{r}N_{r}}} \right)} \\\vdots \\{\exp \left( {{j\left( {N_{r} - 1} \right)}\frac{2\; \pi \; l}{\Delta_{r}N_{r}}} \right)}\end{bmatrix}}\begin{bmatrix}1 \\{\exp \left( {j\frac{2\; \pi \; l}{\Delta_{c}N_{c}}} \right)} \\\vdots \\{\exp \left( {{j\left( {N_{c} - 1} \right)}\frac{2\; \pi \; l}{\Delta_{c}N_{c}}} \right)}\end{bmatrix}}^{T}},{l = 0},1,\ldots \mspace{14mu},{{\Delta_{r}N_{r}} - 1},{k = 0},1,\ldots \mspace{14mu},{{\Delta_{c}N_{c}} - 1}} & (7)\end{matrix}$

As mentioned above, oversampling factors of 1 correspond tonon-overlapping beams, i.e., critically-sampled DFT vectors. Similarly,the number of channel coefficients c_(k,l) ^((q,f)) that need to bequantized is 2KL×N_(RX)N_(F) instead of 2N_(r)N_(c)×N_(RX)N_(F). When(θ_(max)−θ_(min)) and (φ_(max)−φ_(min)) are relatively small, it isexpected that KL<<N_(r)N_(c) (which results in some savings in feedbackrequirements).

In both embodiments 1 and 2 described above, the values {k₀, K, l₀, L}are chosen for each UE such that the small angular cone of AoDs definedby {(φ,θ): φε[φ_(min),φ_(max)]̂θε[θ_(min), θ_(max)]} is covered.

The channel representation parameters can be defined as follows. Twoalternatives can be devised:

-   -   (Alt 1) The main parameters are those which represent or are        associated with the AoD parameters (θ_(min), θ_(max), φ_(min),        φ_(max)). For example, four parameters—each representing one of        those four DL AoD parameters—can be defined where each parameter        represents an index to the AoD value.        -   For example, in case of (1)-(7), these parameters are {k₀,            K, l₀, L}.        -   In addition to the four AoD parameters, a sub-sampling            parameter may be defined and signaled to each UE. This            sub-sampling parameter allows the eNB to configure each UE            for a sparser subset selection. This is especially relevant            when the master-set is heavily oversampled. For example,            sub-sampling of 2 indicates that out of all the possible            basis function indices in (4) or (7), only those            corresponding to {k₀, k₀+2, . . . , K−2, K} and {l₀, l₀+2, .            . . , L−2, l} are configured for the UE of interest.    -   (Alt 2) Alternatively, rather than signaling the DL AoD        parameters and their companion parameters, it is also possible        for the eNB to signal a parameter or a bitmap to each of the UEs        which indicates the subset choice. For instance, if the        master-set consists of 128 vectors, a 128-bit bitmap may be        signaled to indicate the subset selection. If a restricted        choice of subset is to be employed, the number of bits for        representing the signaling parameter can be reduced.        -   In case of the bitmap approach, two different bitmaps can be            defined for φ and θ dimensions, respectively. Alternatively,            a single two-dimensional bitmap for (φ,θ) can be used for            better flexibility. This is especially applicable when the            eNB configures a particular UE with a plurality of angular            cones (as mentioned above).

The channel representation parameters can be signaled to by the eNB toeach UE in several ways (including any combination of below):

-   -   (Alt 1) A higher-layer signaling (e.g., via RRC signaling) is        used to update the quantization parameters per UE.    -   (Alt 2) D-BCH signaling in LTE is able to accommodate such        (quantization parameters slowly updated). The quantization        parameters are signaled via PDSCH where the UE of interest is        notified via some paging mechanism (e.g. PDCCH-based) to look        for the update.    -   (Alt 3) When aperiodic PUSCH-based (shared data channel) CSI        reporting (e.g. in TS36.213 section 7.2.1) is configured for the        UE, the quantization parameters can be included in the UL grant        that triggers the CSI report.

Embodiment 3

Starting from either embodiment 1 or 2, another level of reduction indimensionality may be achieved if the channel representations in(1)/(1b) or (5) is applied to the channel eigenvectors rather than thechannel itself. Using (1b) to illustrate the method (which should bereadily extended to the case with (1) or (5) by those skilled in theart), the procedure is as follows:

-   -   Eigen-decomposition or singular-value decomposition is performed        to the DL MIMO channel for each polarization and frequency        subband. Here the channels associated with different receive        antennas are concatenated into one channel matrix.    -   Based on the chosen RI (for example, either N=1 or 2), the UE        selects N dominant (strongest) eigenvectors (or the right        singular vectors) and the corresponding eigenvalues are        reflected/captured in the N CQI values that are reported along        with the RI.    -   Since the UE is situated within one or a few small angular        cones, each of the N eigenvectors (for each polarization and        frequency sub-band) allows the following approximation (cf.        equation (1b)).

v ^((f))≅Σ_((k,l)εΩ) d _(k,l) ^((f))vec{A(φ_(k),θ_(l))}  (7b)

Here vec{X} converts the matrix X into a vector by stacking all thecolumn vectors of X.

-   -   For each of the N eigenvectors, the coefficients d_(k,l) ^((f))        are then quantized by the UE and reported to the eNB.    -   Once eNB receives the report from the UE, eNB reconstructs each        of the N eigenvectors according to (7b).

In general, this embodiment captures the UE feedback and eNBreconstruction of N quantized precoding vectors for N transmissionlayers, where each of the N precoding vectors (with a special case ofN=1 or 2) is quantized according to the channel representation in(1)/(1b) or (5) as embodied in (7b). The associated CQI value(s)correspond to the value of RI and the choice of the N precoding vectors.The above embodiment where the precoding vectors are eigenvectors ismerely exemplary.

For all the aforementioned embodiments (1, 2, and 3), a quantizationscheme is needed. Given the above channel representation parameters, thecoefficients

{c_(k, l)^((q, f))}

are to be computed by the UE (see below for details), then thosecoefficients are quantized at the UE based on a predeterminedmethod/procedure (which needs to be specified). Different quantizationprocedures (either scalar or vector quantization) can be used toefficiently “compress” the coefficient feedback to the eNB.

The quantization of coefficients

{c_(k, l)^((q, f))}

requires a quantization codebook C, which may be constructed to minimizea metric such as (8) below or to minimize codebook search time or toexploit the dependencies between samples to be quantized or to meet anyother design criterion. A few exemplary codebook design considerationsand alternatives are provided below. Those skilled in the art willrecognize that any other codebook alternatives are also within the scopeof this disclosure.

-   -   Since the coefficients

{c_(k, l)^((q, f))}

are complex, first the real and imaginary parts may be separated, andthen scalar quantized using the same or two different scalar codebooks.The scalar codebooks may be uniform or non-uniform in (r_(l), r_(h))where r_(l)<r_(h) are real numbers.

-   -   Alternatively, the real and imaginary parts of coefficients may        first be separated, then vectorized in vectors of fixed length        N, and finally vector quantized using vector codebooks. The        vector codebooks may be uniform or non-uniform in an        N-dimensional region in Euclidean space.        -   In one design, the vector codebooks are different for real            and imaginary components.        -   In another design, the same vector codebook is used for both            real and imaginary components.            -   In one vectorization method, the vectors consist of                either all real or all imaginary components of                coefficients.            -   In another vectorization method, the vectors consist of                both real and imaginary components of coefficients. For                example, the real and imaginary components of the same                coefficient are placed next to each other either in the                same vector or in two adjacent vectors (real component                is the last element of the vector and imaginary                component is the first element of the adjacent vector).            -   In another vectorization method, the real and imaginary                components are placed according to a pre-defined                permutation.    -   Alternatively, the amplitudes and phases of the coefficients may        be quantized using amplitude and phase codebooks, respectively.        -   The amplitude codebook may be a scalar codebook where the            amplitude of each coefficient is quantized separately. The            amplitude codebook may be uniform or non-uniform in (a_(l),            a_(h)) where 0≦a_(l)<a_(h) are positive numbers.        -   Alternatively, it may be a vector codebook where we first            vectorize amplitudes (of fixed length N) of all coefficients            and then quantize them using a vector amplitude codebook,            which may be uniform or non-uniform in an N-dimensional            region in positive orthant.        -   The phase codebook may be uniform or nonuniform in (a_(l),            a_(h)) where 0≦α_(l)<α_(h)≦2π.    -   In above-mentioned or other codebook designs, the vectorization        and quantization at the UE and the reconstruction and        de-vectorization (extracting real and imaginary components) at        the eNB must be aligned.    -   Since different vectorization and quantization methods will        result in different codebooks, the vectorization and        quantization methods may be configurable by eNB and the        configuration may be signaled to the UE together with the        channel representation parameter signaling (see above).        Depending on the configured vectorization and quantization        methods, the UE vectorizes the coefficients and uses the        corresponding codebook to quantize the vectors.    -   The designed codebook may be basis-agnostic or basis-aware. If        it is basis-agnostic, then it is desired to design one codebook        that is universally applicable to all UEs regardless of their        configured basis (A(φ_(k), θ_(l)) or B_(k,l)). If it is        basis-aware, then codebook design may be specific to the basis        and may change from basis to basis.    -   In some designs, the codebook may be fixed and non-adaptive over        time, and it may be designed once based on some channel        statistics such as second moments. In other designs, it may be        adaptive over time, and hence updated periodically or        aperiodically based on real channel measurements. This codebook        adaptation may be configurable by the eNB together with the        channel representation parameter signaling (see above) or        separately.    -   In some designs, the codebook may be non-adaptive        (pre-determined) but only a subset of the codebook is used for a        given DL channel coefficient quantization. In this case,        different subsets of the codebook are used by the UE of interest        across consecutive quantizations (and reporting instances). Upon        receiving the feedback, the eNB may take into account reports        over multiple instances to derive a higher resolution        representation of the corresponding DL MIMO channel. For        example, a linear filtering may be performed at the eNB across        multiple reporting instances. Since different subsets are used        across multiple reporting instances, feedback overhead can be        reduced for a given desirable resolution. It also allows the eNB        to reconstruct and update the DL MIMO channel coefficients at        the highest possible reporting rate.    -   The channel coefficient computation and quantization may be        performed separately in which channel coefficients are computed        first, for example according to (9) below, and then the computed        channel coefficients (ĉ^((q,f))) are quantized. Alternatively,        the quantized channel coefficients are directly obtained, for        example using the codebook in place c_(k,l) ^((g,f)) in (8).    -   If the UE's channel resides in multiple cones, i.e., a set of        AoD parameters {(θ_(min), θ_(max), φ_(min), φ_(max))}, then the        channel coefficient quantization and feedback may be joint or it        may be cone-specific.

A few example codebook choices are provided below. The details of theirdesign are skipped and are available in literature.

Scalar Gaussian Codebook:

Assuming independent and identically distributed standard normal channelcoefficients, the designed scalar codebook (see FIG. 4) may be:

-   -   uniform, in which case the quantization points are uniformly        spaced (Δ) on the real line, or    -   non-uniform, in which case the quantization points are        non-uniformly spaced (Δ₁, Δ₂, Δ₃, . . . ) on the real line.        Before quantizing the channel coefficients using scalar Gaussian        codebook, the channel coefficients are normalized by the        estimated channel variance. The quantized value of the estimated        channel variance is also fed back to the eNB together with the        quantized channel coefficients. The eNB uses both of them to        reconstruct the channel coefficients.

Vector Gaussian Codebook:

Assuming independent and identically distributed standard normal channelcoefficients, the designed vector codebook (see 2D example in FIG. 5)may be:

-   -   uniform, in which case the quantization points are uniformly        spaced (Δ) in N-dimensional Euclidean space, or    -   non-uniform in which the quantization points are non-uniformly        spaced (Δ₁, Δ₂, Δ₃, . . . ) in N-dimensional Euclidean space.        Before quantizing the channel coefficients using vector Gaussian        codebook, the vectorized channel coefficients are pre-multiplied        by the negative square root of estimated channel covariance        matrix. The quantized value of the estimated channel covariance        is also fed back to the eNB together with the quantized channel        coefficients. The eNB uses both of them to reconstruct the        channel coefficients.

Training-Based Codebook:

In some designs, the codebook construction may be training-based usingactual channel measurements. A few example training-based codebooks areas follows.

-   -   Iterative Lloyd-Max codebook: The algorithm starts with the        initial codebook selection, for example from the training data        (scalar or vector). This is followed by data partitioning using        the initial codebook based on some metric such as minimum        distance. The codebook is then updated using the partitioned        data, for example, the updated code points may be the centroid        of the partitions. The algorithm continues to iterate until some        stopping criterion is met. An illustration of the Lloyd-Max        algorithms is provided in FIG. 6.    -   Shape-gain codebook: If the dynamic range of the channel        coefficients is large, then the magnitude (gain) and the        direction (shape) of data vectors may be separately quantized.        The gain codebook is scalar codebook and the shape codebook is a        vector codebook, both can be designed using the Lloyd-Max        algorithm.    -   Structured codebook: In order to reduce the codebook search        complexity (especially for vector codebooks), the codebook may        be multi-level and structured such that the lower level        codebooks are smaller than the upper level codebooks and they        partition the upper level codebooks uniformly. The codebook        search starts at the lower levels, and the “best” codewords in        the lower levels are used to restrict the codebook search in        upper level codebooks. Such structured codebooks can also be        designed using the Lloyd-Max algorithm.

Basis-Aware:

The codebook construction can be basis-aware the basis information isincluded while designing the codebook.

UE and eNB Procedures

As mentioned above, the UE is to report the quantized channelcoefficients

{c_(k, l)^((q, f))}

to the eNB. While LTE (or any wireless standard) specifications do nottypically specify how channel coefficients are computed, those channelcoefficients are typically computed to minimize some type of errormeasure for the representation given either in the first or the secondembodiment in the exemplary embodiments described above. One possibilityis to use the following least-square error criterion:

$\begin{matrix}{\min_{\{ H_{k,l}^{({q,f})}\}}{{H^{({q,f})} - {\sum\limits_{k = k_{0}}^{k_{0} + K - 1}\; {\sum\limits_{l = l_{0}}^{l_{0} + L - 1}\; {c_{k,l}^{({q,f})}B_{k,l}}}}}}_{F}^{2}} & (8)\end{matrix}$

Note that the above example (8) assumes the representation associatedwith embodiment 2 given in (5). Those who are skilled in the art shouldbe able to see a straightforward extension to embodiment 1 given in (1).

In case of multiple-cone configuration, equation (8) may be applied toeach of the plurality of cones.

Given an estimate of H^((q,f)) derived by the UE (e.g., through somechannel estimation), the UE may compute the least-square solution of (8)as follows:

$\begin{matrix}{\mspace{79mu} {{{\hat{c}}^{({q,f})} = {\left( {\Sigma^{{({q,f})}H}\Sigma^{({q,f})}} \right)^{- 1}\Sigma^{{({q,f})}H_{h^{({q,f})}}}}}\mspace{20mu} {{{\hat{c}}^{({q,f})} = \begin{bmatrix}c_{k_{0},l_{0}}^{({q,f})} \\\vdots \\c_{k_{0},{l_{0} + L - 1}}^{({q,f})} \\\vdots \\c_{k_{0 + K - 1},l_{0}}^{({q,f})} \\\vdots \\c_{{k_{0} + k - 1},{l_{0} + L - 1}}^{({q,f})}\end{bmatrix}},{h^{({q,f})} = {{vec}\left\lbrack H^{({q,f})} \right\rbrack}},{\Sigma^{({q,f})} = \left\lbrack {{vec}\left\{ B_{k_{0},l_{0}} \right\} \mspace{14mu} \ldots \mspace{14mu} {vec}\left\{ B_{k_{0},{l_{0} + L - 1}} \right\} \mspace{14mu} \ldots \mspace{14mu} {vec}\left\{ B_{{k_{0} + K - 1},l_{0}} \right\} \mspace{14mu} \ldots \mspace{14mu} {vec}\left\{ B_{{k_{0} + K - 1},{l_{0} + L - 1}} \right\}} \right\rbrack}}}} & (9)\end{matrix}$

Here vec{X} converts the matrix X into a vector by stacking all thecolumn vectors of X. As mentioned above, the number of expansioncoefficients in h^((q,f))(KL) is chosen to be significantly less thanN_(r)N_(c) (the original number of channel coefficients) which resultsin reduction in dimensionality.

Once the eNB receives and decodes the feedback of

{C_(k, l)^((q, f))}

from the UE, the eNB may reconstruct the DL MIMO channel according tothe representation equation in (5) (or in (1) for embodiment 1). Thenthe eNB may perform link adaptation (including precoding) and scheduling(including MU-MIMO) based on the reconstructed DL MIMO channel from eachUE.

CSI-RS Issue

To obtain an estimate of H^((q,f)), the UE may use different types ofreference signals (RS). Among the available reference signals in LTE(CRS, CSI-RS, DM-RS, locationing/positioning RS, discovery RS), CSI-RSseems to be the best candidate for the proposed scheme. In this case,the eNB configures a set of CSI-RS resources for the antenna portsassociated with each UE. Since CSI-RS resources could be rare, the eNBmay utilize a resource reduction technique to send CSI-RS (to cover allthe necessary antenna ports) which can be done in time and/or spatialdomain. In that case, the UE may perform interpolation to recover allthe necessary MIMO channel coefficients H^((q,f)).

Joint Operation: Two Examples

FIGS. 7A and 7B illustrate two exemplary operations of theabove-proposed scheme. Here, operation refers to overalltransmit-receive operations at the eNB and the UE. FIG. 7A exemplifieschannel quantization 700 whereas FIG. 7B exemplifies eigenvectorquantization 710. In either case, the eNB measures the DL AoD profilefor UE-k (including the AoD spread) from at least one uplink signal(step 701). Based on that measurement, the eNB performs a basis subsetselection for UE-k from a fixe predetermined master-set of basisvectors/matrices (step 702). This common master-set is pre-known at theeNB and all UEs. Once the subset is selected, the selection is signaledto UE-k (either via higher layer signaling or a UL grant).

Upon receiving and successfully decoding the configuration parameter(that informs UE-k of its basis subset) and measuring the associated DLchannel from CSI-RS (step 703), UE-k responds by computing the basisexpansion coefficients relative to the configured basis subset (step 704or step 711). These coefficients are then quantized according to apredetermined quantization scheme (step 704 or step 711), and fed backto the eNB via an uplink channel (step 705 or step 712).

Upon receiving feedback from UE-k (as well as from other UEs), the eNBreconstructs either the channel or the eigenvector (step 706 or step713). This is used for link adaptation and scheduling (step 707).

Other Variations

DL Interference Information

The above discussion assumes quantization of the DL MIMO channelH^((q,f)). For DL link adaptation and scheduling, the eNB requires notonly the DL MIMO channel, but also the DL interference profile seen bythe associated UE. Since the UE is able to derive a DL interferenceestimation (e.g., interference covariance matrix, interference power),the UE may report the quantized coefficients

{C_(k, l)^((q, f))}

derived from the pre-whitened estimate of the DL MIMO channel H^((g,f))(or in general, the DL MIMO channel estimate properly scaled by the DLinterference estimate). For instance, if the DL interference covariancematrix estimate for a given polarization, receive antenna, and subbandis R^((q,f)), the DL channel coefficient computation in (9) is performedbased on (R^((q,f)))^(−1/2)H^((q,f)) rather than simply H^((q,f)).

In case of FD-MIMO, it is expected that the DL interference profile seenby each UE may be wideband (rather than frequency selective) due to thenarrow beam which the eNB applies to the UE. In that case, R^((g,f)) maysimply be σ^((q,f)2). Hence, pre-whitening is reduced to a scalarmultiplication which can be done after the coefficient computation in(9) is done. That is, the UE will simply report/feedback

$\left\{ \frac{C_{k,l}^{({q,f})}}{\sigma^{({q,f})}} \right\}$

to the eNB.

Concurrent Operation with Rel.12 CSI Reporting

While the proposed explicit channel feedback facilitates full linkadaptation and scheduling at the eNB, it may be beneficial to operate itin conjunction with Rel.12 CSI reporting. Some reasons are as follows:

-   -   Concurrent operation with Rel.12 CSI may simplify testing        (performance requirements or inter-operability)    -   Rel.12 CSI may be used to at least convey DL interference        information and/or any relevant scaling factor

In this case, the eNB configures the UE of interest with two reportingschemes: 1) DL channel feedback as described above, and 2) Rel.12 CSIfeedback schemes (e.g., one periodic PUCCH-based and one aperiodicPUSCH-based). The following exemplary embodiments are possible.

-   -   With periodic PUCCH-based reporting. In conjunction with        explicit DL channel feedback, a periodic CSI reporting is        configured. Two possibilities exist:        -   Without PMI (mode 1-0 or 2-0): Here RI signals a recommended            transmission rank to the eNB (assuming a single-user            transmission). CQI may indicate a recommended spectral            efficiency (modulation and coding scheme, or “MCS”) assuming            a given precoding at the eNB with a single-user            transmission). This given precoding may either be a fixed            precoding vector/matrix or a maximum ratio transmission            (MRT) precoding vector/matrix.            -   Once the eNB receives this report along with the                quantized DL channel, the eNB may infer the interference                level experienced by the UE (whether it is wideband for                1-0 or narrowband for 2-0).            -   It is also possible for the eNB to restrict RI to either                1 or 2—either based on other configuration parameter(s)                or the Rel.12 codebook subset restriction feature.        -   With PMI (mode 1-1 or 2-1): When PMI is included, a            reference to the existing Rel.12 precoding codebooks (2-,            4-, or 8-antenna port codebooks) is used. Essentially, PMI            is an index to a precoding matrix within a codebook. When            the number of antenna ports associated with FD-MIMO is            larger than 8 (which is most likely the case), the reported            PMI may be utilized to signal a recommended precoding            matrix/vector associated with the horizontal antenna array            dimension (which does not exceed 8 due to the limitation of            Rel.12 precoding codebooks, see FIG. 1). This PMI assumes a            single-user transmission. CQI/RI is used with reference to            the PMI.            -   Once the eNB receives this report along with the                quantized DL channel, the eNB may infer the interference                level experienced by the UE (whether it is wideband for                1-1 or narrowband for 2-1).            -   It is also possible for the eNB to restrict RI to either                1 or 2—either based on other configuration parameter(s)                or the Rel.12 codebook subset restriction feature.    -   With aperiodic PUSCH-based reporting. In conjunction with        explicit DL channel feedback, an aperiodic CSI reporting is        configured. Similar to the periodic reporting, two possibilities        exist:        -   Without PMI (mode 1-0, 2-0, or 3-0): Here RI signals a            recommended transmission rank to the eNB (assuming a            single-user transmission). CQI may indicate a recommended            spectral efficiency (MCS) assuming a given precoding at the            eNB with a single-user transmission). This given precoding            may either be a fixed precoding vector/matrix or a maximum            ratio transmission (MRT) precoding vector/matrix.            -   Once the eNB receives this report along with the                quantized DL channel, the eNB may infer the relative                interference level experienced by the UE (whether it is                wideband for 1-0 or narrowband for 2-0/3-0).            -   It is also possible for the eNB to restrict RI to either                1 or 2—either based on other configuration parameter(s)                or the codebook subset restriction feature.        -   With PMI (mode 1-2, 2-1, 3-1, or 3-2): When PMI is included,            a reference to the existing Rel.12 precoding codebooks (2-,            4-, or 8-antenna port codebooks) is used. Essentially, PMI            is an index to a precoding matrix within a codebook. When            the number of antenna ports associated with FD-MIMO is            larger than 8 (which is most likely the case), the reported            PMI may be utilized to signal a recommended precoding            matrix/vector associated with the horizontal antenna array            dimension (which does not exceed 8, see FIG. 1). This PMI            assumes a single-user transmission. CQI/RI is used with            reference to the PMI.            -   Once the eNB receives this report along with the                quantized DL channel, the eNB may infer the relative                interference level experienced by the UE (whether it is                wideband for 1-2 or narrowband for 2-1/3-1/3-2).            -   It is also possible for the eNB to restrict RI to either                1 or 2—either based on other configuration parameter(s)                or the codebook subset restriction feature.

Alternatively, the existing Rel.12 CSI reporting mechanism (modes) canbe used to report primarily interference information (or in general, anindication of interference level) of the associated UE to the eNB. Inthis case, the CQI field may be used either to indicate a quantizedinterference power or to indicate a recommended MCS level (per Rel.12CQI definition) assuming a pre-defined precoding (as discussed above)and/or transmission rank.

In addition to relying on the currently existing mechanism (as explainedabove), the explicit channel feedback contents may also be designed toinclude CQI/RI. As an example, consider a UE with 2 receive antennas(2-Rx)—although those skilled in the art will be able to extend theschemes below to any number of receive antennas.

In one method (CQURI reporting method 1), a 2-Rx UE is configured toreport per-Rx-antenna quantized channel vector according to (1), and theUE reports the reconstructed channel matrix comprising two column (orrow) vectors. The embodiments below are described in terms of columnvectors only, but the same principle applies when the UE reports two rowvectors of the reconstructed channel matrix.

-   -   In one example, a UE derives and reports rank-1 CQI, assuming        that the eNB applies a precoder being equal to a strongest        eigenvector (corresponding to the strongest of eigenvalues) of        the reconstructed channel matrix.    -   In another example, a UE derives and reports rank-2 CQI,        assuming that the eNB applies a precoder being equal to two        eigenvectors of the reconstructed channel matrix.    -   In another example, a UE derives and reports rank-2 CQI,        assuming that the eNB applies a precoder being equal to the        reconstructed channel matrix comprising two columns.    -   In another example, a UE derives and reports rank-2 CQI,        assuming that the eNB separately applies a precoder being equal        to each column vector of the reconstructed channel matrix. In        some embodiments, the UE derives a first CQI assuming that the        eNB applies a precoder being equal to the first column vector;        and a second CQI assuming a precoder being equal to the second        column. In some embodiments, the UE derives a first CQI assuming        that the UE processes a received signal on the first Rx antenna,        wherein eNB applies a precoder for the received signal, the        precoder being equal to the first column vector; the UE derives        a second CQI in the same way with utilizing the second Rx        antenna and the second column vector.    -   In some embodiments, UE may further assume, for CQI derivation        purposes, that the eNB normalizes the power of each column        vector of the reconstructed channel matrix to be one to use as a        precoder.    -   In one alternative, the UE may derive and report RI and CQI        jointly according to these examples.    -   In another alternative, the UE is configured to report only        rank-2 CQI, so that the channel strength corresponding to        2-layer transmission is separately reported to the eNB.

In another method (CQI/RI reporting method 2), a 2-Rx UE is configuredto report RI number of quantized channel vectors according to (1).

-   -   In one example, when RI=1 is reported, the UE is configured to        quantize and report the eigenvector corresponding to the        strongest eigenvalue of the full channel matrix according to        (1), and corresponding CQI assuming that the eNB applies a        precoder being equal to the aforementioned strongest        eigenvector.    -   For CQI reporting when RI=2, embodiments related to CQI        reporting method 1 can be used.

UE-Assisted Basis Subset Selection Via UE Feedback

The above examples assume that the eNB is able to measure the DL AoDprofile from at least one UL signal due to long-term UL-DL channelreciprocity. This assumption is valid for most FDD deployment scenariosto date since the UL-DL duplex distance is relatively small.

For future systems, however, it is unclear whether such an assumptioncan be maintained, especially when UL and DL channels and cell radii maybe asymmetric (which is reasonable since UL and DL traffics tend to beasymmetric). For instance, assigning a DL carrier in the mmWave regionin conjunction with a UL carrier in the PCS band region is plausible. Insuch scenarios, even long-term UL-DL channel reciprocity cannot bemaintained.

Therefore, an additional uplink feedback from a UE of interest to theeNB is beneficial to assist the eNB in performing basis subsetselection. As previously mentioned, relevant DL AoD profile parametersmay be measured at the UE and reported (fed back) to the eNB.Alternatively, the UE may report a recommended basis subset selection.For instance, a bitmap that represents a selection of basisvectors/matrices from a predetermined master-set (known at the eNB andall the UEs associated with the said eNB) is reported to the eNB.

One exemplary embodiment may be devised based on the Rel.12specification. For illustrative purposes, only rank-1 and rank-2 (themost relevant scenarios for FD-MIMO) are discussed here, although itshould be apparent to those skilled in the art how to extend theseprinciples to higher ranks. TABLE 1 and TABLE 2 are codebooks defined inRel.10/12 LTE specifications for rank-1 and rank-2 (1-layer and 2-layer)CSI reporting for UEs configured with 8 Tx antenna port transmissions.To determine a code word (CW) for each codebook, two indices, i.e., i₁and i₂ have to be selected. In these precoder expressions, the followingtwo variables are used:

φ_(n) =e ^(jπn/2)

v _(m)=[1 e ^(j2πm/32) e ^(j4πm/32) e ^(j6πm/32]T).

TABLE 1 Codebook for 2-layer CSI reporting using antenna ports 15 to 22i₂ i₁ 0 1 2 3 4 5 6 7 0-15 W_(2i) ₁ _(, 0) ⁽¹⁾ W_(2i) ₁ _(, 1) ⁽¹⁾W_(2i) ₁ _(, 2) ⁽¹⁾ W_(2i) ₁ _(, 3) ⁽¹⁾ W_(2i) ₁ _(+1, 0) ⁽¹⁾ W_(2i) ₁_(+1, 1) ⁽¹⁾ W_(2i) ₁ _(+1, 2) ⁽¹⁾ W_(2i) ₁ _(+1, 3) ⁽¹⁾ i₂ i₁ 8 9 10 1112 13 14 15 0-15 W_(2i) ₁ _(+2, 0) ⁽¹⁾ W_(2i) ₁ _(+2, 1) ⁽¹⁾ W_(2i) ₁_(+2, 2) ⁽¹⁾ W_(2i) ₁ _(+2, 3) ⁽¹⁾ W_(2i) ₁ _(+3, 0) ⁽¹⁾ W_(2i) ₁_(+3, 1) ⁽¹⁾ W_(2i) ₁ _(+3, 2) ⁽¹⁾ W_(2i) ₁ _(+3, 3) ⁽¹⁾${{where}\mspace{14mu} W_{m,n}^{(1)}} = {\frac{1}{\sqrt{8}}\begin{bmatrix}v_{m} \\{\phi_{n}v_{m}}\end{bmatrix}}$If the most recently reported RI=1, m and n are derived with the twoindices i₁ and i₂ according to TABLE 1, resulting in a rank-1 precoder,

$W_{m,n}^{(1)} = {{\frac{1}{\sqrt{8}}\begin{bmatrix}v_{m} \\{\phi_{n}v_{m}}\end{bmatrix}}.}$

TABLE 2 Codebook for 2-layer CSI reporting using antenna ports 15 to 22i₂ i₁ 0 1 2 3 0-15 W_(2i) ₁ _(, 2i) ₁ _(, 0) ⁽²⁾ W_(2i) ₁ _(, 2i) ₁_(, 1) ⁽²⁾ W_(2i) ₁ _(+1, 2i) ₁ _(+1, 0) ⁽²⁾ W_(2i) ₁ _(+1, 2i) ₁_(+1, 0) ⁽²⁾ i₂ i₁ 4 5 6 7 0-15 W_(2i) ₁ _(+2, 2i) ₁ _(+2, 0) ⁽²⁾ W_(2i)₁ _(+2, 2i) ₁ _(+2, 1) ⁽²⁾ W_(2i) ₁ _(+3, 2i) ₁ _(+3, 0) ⁽²⁾ W_(2i) ₁_(+3, 2i) ₁ _(+3, 0) ⁽²⁾ i₂ i₁ 8 9 10 11 0-15 W_(2i) ₁ _(, 2i) ₁_(+1, 0) ⁽²⁾ W_(2i) ₁ _(, 2i) ₁ _(+1, 1) ⁽²⁾ W_(2i) ₁ _(+1, 2i) ₁_(+2, 0) ⁽²⁾ W_(2i) ₁ _(+1, 2i) ₁ _(+2, 0) ⁽²⁾ i₂ i₁ 12 13 14 15 0-15W_(2i) ₁ _(, 2i) ₁ _(+3, 0) ⁽²⁾ W_(2i) ₁ _(, 2i) ₁ _(+3, 1) ⁽²⁾ W_(2i) ₁_(+1, 2i) ₁ _(+3, 0) ⁽²⁾ W_(2i) ₁ _(+1, 2i) ₁ _(+3, 0) ⁽²⁾${{where}\mspace{14mu} W_{m,m^{\prime},n}^{(2)}} = {\frac{1}{4}\begin{bmatrix}v_{m} & v_{m^{\prime}} \\{\phi_{n}v_{m}} & {{- \phi_{n}}v_{m^{\prime}}}\end{bmatrix}}$

If the most recently reported RI=2, m, m′ and n are derived with the twoindices i₁ and i₂ according to TABLE 2, resulting in a rank-2 precoder,

$W_{m,m^{\prime},n}^{(2)} = {{\frac{1}{4}\begin{bmatrix}v_{m} & v_{m^{\prime}} \\{\phi_{n}v_{m}} & {{- \phi_{n}}v_{m^{\prime}}}\end{bmatrix}}.}$

It is noted that W_(m,m′,n) ⁽²⁾ is constructed such that it can be usedfor two different types of channel conditions that facilitate a rank-2transmission.

One subset of the codebook associated with i₂={0, 1, . . . , 7}comprises codewords with m=m′, or with the same beams (v_(m)) used forconstructing the rank-2 precoder:

$W_{m,m^{\prime},n}^{(2)} = {{\frac{1}{4}\begin{bmatrix}v_{m} & v_{m} \\{\phi_{n}v_{m}} & {{- \phi_{n}}v_{m}}\end{bmatrix}}.}$

In this case, the two columns in the 2-layer precoder are orthogonal(i.e., [v_(m) φ_(n)v_(m)]^(H)·[v_(m)−φ_(n)v_(m)]=0), owing to thedifferent signs applied to φ_(n) for the two columns. These rank-2precoders are likely to be used for those UEs that can receive strongsignals along two orthogonal channels generated by the two differentlypolarized antennas.

The UE operation according to some embodiments of the current inventionis as follows (assuming the use of 2D antenna array):

-   -   1. UE receives CSI-RS configuration for N_(P) antenna ports and        corresponding CSI-RS.        -   a. N_(P) may be decomposed into N_(P)=N_(H)·N_(V), where            N_(H) is a number of antenna ports along one row and N_(V)            is a number of antenna ports along one column of 2D            rectangular antenna array. In one example, N_(V)=4 and            N_(H)=8, wherein the cross-polarized (“x-pol”) dimension is            counted within a row rather than a column.    -   2. Processing the CSI-RS, the UE derives CQI, PMI, RI, wherein        -   a. RI corresponds to a preferred or recommended rank by the            UE; and        -   b. PMI corresponds to a preferred or recommended precoding            matrix by the UE, each column of which, say w, is            constructed with a linear combination of a number of basis            vectors:

$w = {\sum\limits_{l = 1}^{L}\; {c_{l}{a_{l}.}}}$

-   -   -   -   i. {a_(l)} is a set of basis vectors comprising L                distinct basis vectors selected out of a mother or                master set comprising a large number (>>L) of basis                vectors, and each basis vector a_(l) is an N_(P)×1                vector.                -   a) a_(l) can be further decomposed into: a_(l)=h_(l)                    v_(l), wherein h_(l) and v_(l) are DFT vectors of                    size N_(H)×1 and N_(V)×1 respectively representing                    azimuth and elevation array responses for a given                    pair of azimuth and elevation angles. In this case,                    the master-set may be constructed as a product set:                    {h_(l)                    v_(l): hεW_(H), vεW_(V)}.                -    1) In one example, L=4. Furthermore, v_(l)=v, ∀l,                    wherein vεW_(V); and H={h_(l)}_(l=1,2,3,4)                    corresponds to four beams corresponding to i₁ in LTE                    Rel-10 8-Tx codebook (TABLE 1 and TABLE 2), i.e.,                    H={v_(2i), v_(2i+1), v_(2i+2), v_(2i+3)}, where                -    v_(m)=[1 e^(j2πm/32) e^(j4πm/32) e^(j6πm/32)]^(T).                -   b) a_(l) can be further decomposed into:

$a_{l} = {\begin{bmatrix}h_{l} \\{^{{j\phi}_{l}}h_{l}}\end{bmatrix} \otimes v_{l}}$

-   -   -   -   -    where h₁ and v₁ are DFT vectors of size N_(H)×1 and                    N_(V)×1 respectively representing azimuth and                    elevation array responses for a given pair of an                    azimuth angle and an elevation angle; and

$\phi_{l} \in \left\{ {\frac{2\; m\; \pi}{M}\text{:}\mspace{14mu} \begin{matrix}{m\mspace{14mu} {can}\mspace{14mu} {be}\mspace{14mu} {selected}\mspace{14mu} {from}\mspace{14mu} a} \\{{set}\mspace{14mu} {of}\mspace{14mu} {nonnegative}\mspace{14mu} {integers}}\end{matrix}}\; \right\}$

-   -   -   -   -    represents the co-phase of the x-pol array. In this                    case, the mother set can be a product set:

$\left\{ {{{{\begin{bmatrix}h_{l} \\{^{{j\phi}_{l}}h_{l}}\end{bmatrix} \otimes v_{l} \otimes v}\text{:}\mspace{14mu} h} \in W_{H}},{v \in W_{V}}} \right\}.$

-   -   -   -   -   c) For example, a DFT vector of size 4×1 is v_(m)=[1                    e^(j2πm/D) e^(j4πm/D) e^(j6πm/D)]^(T), where D=2^(n)                    and n is a positive integer. Other size DFT vectors                    can be similarly constructed.

            -   ii. {c_(l)} is a corresponding set of L scaling                coefficients, each element of which is a complex number.                Some alternatives for c_(l) quantization are:                -   a) Real and imaginary components of c_(l) are                    separately quantized, N_(Re) quantization bits for                    the real dimension and N_(Im) quantization bits for                    the imaginary dimension.                -    1) In one method, N_(Re)=N_(Im)                -   b) Amplitude and phase components of c_(l) are                    separately quantized, N_(A) quantization bits for                    the amplitude and N_(Ph) quantization bits for the                    phase.                -   c) Some details for the quantization methods can be                    found above.

        -   c. CQI corresponds to a modulation and coding scheme which            allows the UE to receive a PDSCH packet with a constant            (e.g., 0.1) packet error probability when the selected PMI            and the selected RI is used for precoding.

        -   d. UE may select RI and PMI that allows the best (or            highest) CQI for the PDSCH transmission with a constant            (e.g., 0.1) error probability.

    -   3. The UE report PMI/CQI/RI on a single PUSCH, when triggered        for an aperiodic (PUSCH) report:        -   a. In one method, PMI corresponding to a basis vector set            {a_(l)} is wideband (i.e., only one set is reported in the            aperiodic report), the PMI corresponding to the coefficient            set {c_(l)} is subband (i.e., multiple sets, e.g., one per            subband are reported in the periodic report).

    -   4. The UE report CQI/PMI on a PUCCH in another subframe with a        period P, RI on a PUCCH in one subframe with a period Q, when        configured with a periodic report.

    -   5. In one method, PMI corresponding to a basis vector set is        less frequently reported (i.e., reported with larger period)        than the PMI corresponding to the coefficient set.

Although the present disclosure has been described with an exemplaryembodiment, various changes and modifications may be suggested to oneskilled in the art. It is intended that the present disclosure encompasssuch changes and modifications as fall within the scope of the appendedclaims.

What is claimed is:
 1. A user equipment, comprising: a receiver configured to receive signals from a plurality of transmit antenna elements within a two-dimensional antenna array at a base station, and to receive an indication of a subset selection of vectors; a processor configured to determine channel state information (CSI) for a downlink (DL) multiple input multiple output (MIMO) channel between the user equipment and the two-dimensional antenna array, the CSI corresponding to a subset of vectors that is based upon the received indication of the subset selection; and a transmitter configured to transmit an indication of the CSI to the base station.
 2. The user equipment according to claim 1, wherein the subset selection indication is transmitted to the user equipment via higher layer signaling.
 3. The user equipment according to claim 1, wherein the subset selection indication is contained in an uplink grant for the user equipment.
 4. The user equipment according to claim 1, wherein the CSI comprises a plurality of channel coefficients, where each coefficient corresponds to one vector in the subset selected by the base station and is computed in response to a downlink channel measurement.
 5. The user equipment according to claim 4, wherein the user equipment also reports an indication associated with a recommended subset selection to the base station.
 6. A method, comprising: receiving at a user equipment signals from a plurality of transmit antenna elements within a two-dimensional antenna array at a base station; receiving at the user equipment an indication of a plurality of subset selection of vectors; determining at the user equipment channel state information (CSI) for a downlink (DL) multiple input multiple output (MIMO) channel between the user equipment and the two-dimensional antenna array, the CSI corresponding to a subset of vectors that is based upon the received indication of the subset selection; and transmitting from the user equipment an indication of the CSI to the base station.
 7. The method according to claim 6, wherein the subset selection indication is transmitted to the user equipment via higher layer signaling.
 8. The method according to claim 6, wherein the subset selection indication is contained in an uplink grant for the user equipment.
 9. The method according to claim 6, wherein the CSI comprises a plurality of channel coefficients, where each coefficient corresponds to one vector in the subset selected by the base station and is computed in response to a downlink channel measurement.
 10. The method according to claim 9, wherein the user equipment also reports an indication associated with a recommended subset selection to the base station.
 11. A base station, comprising: a unit configured to select a subset of a master codebook for at least one user equipment, wherein the master codebook consists of a plurality of precoders; a transmitter configured to signal the subset selection to the user equipment via a downlink channel; a receiver configured to decode at least one type of channel state information (CSI) report from the user equipment; and a unit configured to reconstruct channel information for the user equipment from the decoded CSI report and a linear combination of the precoders in the selected subset.
 12. The base station according to claim 11, wherein the subset is chosen based on at least an angle-of-arrival profile measured from at least one uplink signal.
 13. The base station according to claim 12, wherein the angle-of-arrival profile consists of a range of azimuthal angles and a range of elevation angles.
 14. The base station according to claim 11, wherein the subset is chosen based on at least a second type of CSI report.
 15. The base station according to claim 14, wherein the second type of CSI report is reported at a different periodicity from the first type of CSI report.
 16. A method, comprising: selecting a subset of a master codebook for at least one user equipment, wherein the master codebook consists of a plurality of precoders; signaling the subset selection to the user equipment via a downlink channel; decoding at least one type of channel state information (CSI) report from the user equipment; and reconstructing channel information for the user equipment from the decoded CSI report and a linear combination of the precoders in the selected subset.
 17. The method according to claim 16, wherein the subset is chosen based on at least an angle-of-arrival profile measured from at least one uplink signal.
 18. The method according to claim 17, wherein the angle-of-arrival profile consists of a range of azimuthal angles and a range of elevation angles.
 19. The method according to claim 16, wherein the subset is chosen based on at least a second type of CSI report.
 20. The method according to claim 19, wherein the second type of CSI report is reported at a different periodicity from the first type of CSI report. 